Artificial Intelligence Helps to Resolve Long-Running Astrophysics Debate on Supermassive Black Holes
According to astronomers, black holes with masses equal to thousands of suns do put a brake on the formation of new stars. Applying three state-of-the-art simulations and machine learning to back up results from a large sky survey, the scientists determine a 20-year long debate on the birth of stars. Joanna Piotrowska, a Ph.D. scholar at the University of Cambridge, presented the latest work on July 20, 2021, at the virtual National Astronomy Meeting (NAM 2021).
The formation of stars in galaxies has long been a focal point of astronomy study. After years of successful observations and analytical modeling resulted in a better understanding of how gas collapses to create new stars both in and beyond our own Milky Way. However, thanks to all-sky scrutinizing programs like the Sloan Digital Sky Survey (SDSS), astrophysicists understood that not all galaxies in the local Universe are actively star-forming — there exists an abundant population of “quiescent” objects which form stars at significantly lower rates.

The question of what holds the formation of new stars in galaxies remains the biggest unknown in our understanding of galaxy evolution, discussed over the past two decades. Piotrowska and her team perform an experiment to find out what might be responsible.
Using three state-of-the-art cosmological simulations — IllustrisTNG, Illustris and, EAGLE— the astronomers examined what we would anticipate seeing in the real Universe as observed by the SDSS when various physical methods were halting stars formation in massive galaxies.
The astrophysicists used a machine-learning algorithm to analyze galaxies into star-forming and quiescent, asking which of three parameters: the mass of the supermassive black holes found at the center of galaxies (these monster objects have typically millions or even billions of times the mass of our Sun), the total mass of stars in the galaxy, or the mass of the dark matter halo around galaxies, best predicts how galaxies turn out.

These parameters then allowed the team to work out which physical process: shock heating of gas in massive halos, energy injection by supermassive black holes, or supernova explosions is responsible for pushing galaxies into semi-retirement.
The latest simulations predict the supermassive black hole mass as the most crucial factor in putting the obstacles on star formation. Crucially, the simulation outcomes match observations of the local Universe, adding weight to the scientists’ findings.

Piotrowska says: “It’s very interesting to see how the simulations predict exactly what we observe in the real Universe. Supermassive black holes — objects with masses equal to thousands or even millions of Suns — really do have a significant effect on their surroundings. These monster objects push their host galaxies into a kind of semi-retirement from star formation.”
Meeting: Royal Astronomical Society National Astronomy Meeting